Blog Posts

  • Dec 14: Holiday! This is my last post for this calendar year. There isn’t much in it other than my announcement that I won’t post anything new for a couple of weeks. Have a good holiday, whatever you are celebrating.

  • Dec 11: Completions I evaluated data about the number of students who were enrolled in classes for the first 45 days of the term.

  • Dec 7: Enrollment Trends This is a look at enrollment trends since 2010 for the college’s locations and subjects.

  • Dec 4: Personal Email Network I used Python to generate three different word clouds that describe my personal email network.

  • Nov 30: IPEDS Feedback Report This has a link to the IPEDs feedback report along with just a couple of highlights from that report.

  • Nov 26: Fast Facts This has links to two different Fast Facts reports from the Cochise College Department of Institutional Research.

  • Nov 20: Survey of Student Engagement This links to the executive summary for Cochise College’s Survey of Student Engagement.

  • Nov 16: Google Analytics I took a look at the Google Analytics for the Cochise College website and made a couple of interesting discoveries.

  • Nov 13: Moodle Logins I used some data from the Intelliboard system to analyize login trends for our Moodle system.

  • Nov 9: Industry Supply Chain Impact This is a look at the fiscal impact on the Cochise County supply chain from a single industry: defense.

  • Nov 7: Blogdown and Bookdown I use blogdown and bookdown to help me with posting writing to my site. This is a brief description of those two important tools.

  • Nov 2: The Scatterplot Matrix A splom visualizes several scatter plots at one time to facilitate comparison.

  • Oct 30: Career Coach Cochise College makes a public website available to explore career options and the courses that we offer to support those careers.

  • Oct 26: Art With R While R is a great analysis tool, sometimes it is fun to just play around and create some pretty graphics.

  • Oct 22: Discipline Success How successful are our students when they transfer to the university?

  • Oct 19: Medical Billing This post presents a report analyzing the viability of a “medical billing” certificate.

  • Oct 16: Simple Regression Several simple regression models are developed and then predictions are made based on those models.

  • Oct 12: Data Exploration In this post, I take a look at a sample data set and describe a few of the initial steps I take in analyzing data.

  • Oct 9: About Data… This post defines the various types of data, which is critical for data analysis.

  • Oct 5: Fun Moodle Stats Several Intelliboard graphs are presented as a fun dip into our Moodle usage.

  • Oct 2: Completions and Jobs This presents the number of job-related completions for Cochise College programs in several disciplines.

  • Sept 29: Cochise County Economic Overview An Economic Overview report for Cochise County is linked in this post.

  • Sept 25: Top and Bottom Growth Occupations Find the fastest growing (and shrinking) occupations in Cochise County.

  • Sept 21: Skills Gap Analysis The skills in demand by employers are compared to those listed on resumes.

  • Sept 18: University Transfer Student Characteristics This post lists a number of characteristics of our transfer students.

  • Sept 14: Exploring Intelliboard Intelliboard is the analytic dashboard linked to our Moodle system.

  • Sept 11: Math Transfer An alluvial chart is used to illustrate the success of our math students who transfer to a university.

  • Sept 7: Registration vs. Unemployment An animation is used to chart registrations as a function of the unemployment rate.

  • Sept 4: Continuous Improvement This is a brief description of the Cochise College strategic planning process.

  • Aug 31: About Correlation The word “correlation” is defined and a correlogram is used to make comparing many variables easy.

  • Aug 28: Registration Exporation A line chart and mosaic plot are used to explore registration statistics.

  • Aug 24: Introduction to Our IPEDS Peers We are part of a group of 29 peer institutions that are introduced in this post.

  • Aug 21: Moving Day! My first post in this blog — this started it all!


R Training

These tutorials include guided practice areas where R commands can be entered to “try out” the commands taught in the various lessons.

Introduction to R This tutorial demonstrates first steps for new R users.

Central Measures One of the easiest R tasks is to calculate the mean and median for a variable so this tutorial is a good place for beginning R users.

Data Dispersion One important data process is measuring their spread. This tutorial demonstrates how R handles range, quartiles, inter-quartile range (IQR), and standard deviation.

Visualizing Descriptives A boxplot is one of the most useful visualizations available to a data analyst and this tutorial demonstrates how they are created.

Frequency Tables This tutorial generates frequency tables, including multi-dimensional and aggregated tables. The round function is also introduced.

Visualizing Frequency This shows how to use several different frequency visualizations, including bar plot, pie chart, heat map, and mosaic plot.

Correlation and Regression This shows how to calculate the correlation between two variables and also how to use a simple regression to predicate the value of one variable when given a second.

Visualizing Data This shows how to create several different continuous data visualizations, including histogram, density plot, line graph, scatter plot, and Q-Q plot.

Parametric Hypothesis Testing This tutorial describes hypothesis testing and the importance of the p-value in a test, then demonstrates how to complete two different parametric tests: ANOVA and t-test and when it is appropriate to use each test.

Nonparametric Hypothesis Testing This tutorial demonstrates how to complete two different nonparametric tests: Kruskal-Wallis H and Mann-Whitney U and when it is appropriate to use each test.

R Demonstrations

These are step-by-step tutorial guides of R projects I’ve done. They are intended to help readers complete similar projects on their own.

  • Activating the Google API This shows the steps I took to be able to programmatically access my gmail account through Python. The Google API can be used to access all sorts of Google services.

  • Blogdown This shows the steps I took to create a blog at Netlify and then link that to GitHub so I can use blogdown on my local computer.

Python Demonstrations

These are step-by-step tutorial guides of Python projects I’ve done. They are intended to help readers complete similar projects on their own.

  • Word Cloud from Gmail Headers I downloaded the headers from all of my sent mail for October, 2016, 2017, and 2018 and created a word cloud to see who I was communicating with.